import matplotlib.pyplot as plt
plt.ion()
leaf_count = myTree.tree.count_terminals()
label_func = lambda x: x.name[:20] if (leaf_count < 30 & x.is_terminal(
)) else ''
branch_label_func = lambda x: (
','.join([a + str(pos) + d for a, pos, d in x.mutations[:10]]) +
('...'
if len(x.mutations) > 10 else '')) if leaf_count < 30 else ''
plot_vs_years(
myTree, show_confidence=False,
label_func=label_func) #, branch_labels=branch_label_func)
plt.savefig(base_name + '_tree.pdf')
else:
# convert branch length to years (this is implicit in the above plot)
myTree.branch_length_to_years()
# decorate tree with inferred mutations
outaln_name = base_name + '_ancestral.fasta'
AlignIO.write(myTree.get_reconstructed_alignment(), outaln_name, 'fasta')
for n in myTree.tree.find_clades():
if n.up is None:
continue
if len(n.mutations):
n.name += '_' + '_'.join(
[a + str(pos) + d for (a, pos, d) in n.mutations])
# write tree to file. Branch length will now be scaled such that node
# positions correspond to sampling times.
outtree_name = base_name + '_timetree.newick'
Phylo.write(myTree.tree, outtree_name, 'newick')
# rerooting can be done along with the tree time inference
tt.run(root="best", branch_length_mode='input')
# if more complicated models (relaxed clocks, coalescent models) are to be used
# or you want to resolve polytomies, treetime needs to be run for
# several iterations, for example as
# tt.run(root="best", resolve_polytomies=True, max_iter=2)
# each node is now at a position that correspond to the given or inferred date
# the units of branch length are still clock rate.
print("clock rate: %1.5f" % tt.date2dist.clock_rate)
fig, axs = plt.subplots(1, 2, figsize=(18, 9))
Phylo.draw(tt.tree,
label_func=lambda x: '',
show_confidence=False,
axes=axs[0])
axs[0].set_title("Tree: units are substitutions", fontsize=18)
# we can convert the branch length to units in years and redraw
tt.branch_length_to_years()
Phylo.draw(tt.tree,
label_func=lambda x: '',
show_confidence=False,
axes=axs[1])
axs[1].set_title("Tree: units are years", fontsize=18)
axs[0].tick_params(labelsize=14)
axs[1].tick_params(labelsize=14)
fig.tight_layout()
# treetime implements a convenience function to plot timetrees
from treetime.treetime import plot_vs_years
plot_vs_years(tt, label_func=lambda x: "", show_confidence=False)
